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Association Between Symptoms of Patients With Heart Failure and Patient Outcomes Based on Electronic Nursing Records

We examined the association between symptoms (ie, dyspnea and pain) and patient outcomes (ie, length of stay, 30-day readmission, and death in hospital) among patients with heart failure using EMRs. This was a descriptive study that was conducted from July 1, 2014, to November 30, 2017. Participants...

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Detalles Bibliográficos
Autores principales: Baik, Seung Yeon, Ryu, Gi Wook, Lee, Hyangkyu, Lee, Siwook, Choi, Mona
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8663513/
https://www.ncbi.nlm.nih.gov/pubmed/34029266
http://dx.doi.org/10.1097/CIN.0000000000000763
Descripción
Sumario:We examined the association between symptoms (ie, dyspnea and pain) and patient outcomes (ie, length of stay, 30-day readmission, and death in hospital) among patients with heart failure using EMRs. This was a descriptive study that was conducted from July 1, 2014, to November 30, 2017. Participants were 754 hospitalized patients with heart failure (mean age, 70.62 ± 14.78 years; male-to-female ratio, 1:1.1). Data were analyzed using descriptive statistics, χ(2) tests, and logistic regression analyses. Patients' average length of stay was 8.92 ± 13.12 days. Thirty-two patients (4.2%) were readmitted, and 100 patients (13.3%) died during hospitalization. Two-thirds (67.7%) experienced dyspnea, and 367 (48.7%) experienced pain. Symptoms and ICU admission were significantly related to patient outcomes. In the regression analyses, dyspnea, pain, and ICU admission were significantly related to higher-than-average lengths of stay. Dyspnea and ICU admission were related to death in hospital. Information regarding patients' symptoms, which was extracted from records, was a valuable resource in examining the relationship between symptoms and patient outcomes. The use of EMRs may be more advantageous than self-reported surveys when examining patients' symptom and utilizing big data.